The State of AI in Marketing and Advertising
What 54 Practitioners Actually Think
The Q1 2026 Morgan Digital and AI Marketers Guild Survey cuts through the noise with data from marketing and advertising professionals across agencies, brands, publishers, platforms and consultancies.
Here's what we found …
Content creation is the breakout use case. Media planning and measurement are the blind spots. More than half of respondents (52%) have reached an advanced maturity level in content creation, making it the furthest-along function in the survey. Strategy and ideation follows at 44%. But media planning (19%) and measurement (22%) lag significantly. The industry is producing more with AI while they’re largely flying blind on whether any of it is working.
Agencies are pulling ahead. Consultants are playing catch-up. Among segments with meaningful response volume, agencies report they are squarely in the “Implementing” stage — well ahead of brands and consultancies. Publishers track closest to agencies while advertisers and consultants cluster near the "Experimenting" mark. We suspect that client pressure, competitive incentives and talent density is what’s driving agencies to push farther faster.
There’s a big gap between doing and measuring. AI adoption is accelerating across the marketing industry, but a striking 24% of respondents say they are not currently measuring its impact in any meaningful way. That number climbs even higher among larger organizations, where change management complexity outpaces the speed of implementation. Everyone is moving fast. Fewer people are keeping score.
The #1 strategic priority is automation. Building AI products is second. 43 respondents listed process automation as a top priority for the year ahead, followed by building AI-enabled products and services (27) and improving data quality and performance signal (21). Governance, ethics and compliance ranked last, suggesting the industry is still in a build-first phase before regulation and accountability catch up.
Skills and budget are the primary barrier, by a wide margin. 44 of 54 respondents cited skills, resources or budget as a barrier to AI progress. Change management (22 mentions) and vendor complexity (22 mentions) round out the top three. Leadership and strategy gaps came up 19 times. The clearest through-line: organizations know AI matters, but many lack the internal infrastructure to act on that belief systematically.
What practitioners are saying. The open-ended responses are where things get interesting. Several respondents pushed back on the hype, with one noting the industry is "sold as another shiny object, when studies are showing less than 10% of people and use cases have any real merit to the output." Another captured the challenge succinctly: "too many tools, very little credible voices to help us narrow it down." At the same time, enthusiasm was real among those further along. One respondent described AI as having "completely empowered everyone in the organization to be a product builder." Another said it's like having an MBA student available for analysis at all times. The divide between believers and skeptics isn't about the technology. It's about implementation depth.
Want to explore the results yourself?
These are just a few of the headlines. The complete survey analysis tool lets you filter results by organization type, company size and role, to compare maturity across functions, and to drill into the verbatim responses behind the numbers.
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